Texas Sharpshooter Fallacy

We’re not always as smart as we think we are. Homo economicus, the always-rational, theoretical economic being, knows it best.

Homo Economicus doesn’t fall prey to the Texas sharpshooter fallacy like we wishful humans do. The term comes from a joke about a Texan who shoots a bunch of bullets into a barn wall, then paints a target where the most bullet holes are after-the-fact, and calls himself a sharpshooter.

The Texas sharpshooter fallacy happens when we zero-in on similarities in data, while conveniently ignoring the differences in data, which can lead us to the wrong conclusions. While science and data-crunching are great, they can lead to biased interpretations at the hands of our monkey-brains, which are always looking for patterns. The Texas sharpshooter fallacy is a problem everywhere, from politics to statistics.

For instance, if you look at a plot of randomly plotted data points, chances are they won’t be nicely spread out. Some areas will have more data points that others. Yet the data is random...there is no pattern of cause, like our brains want to believe there is. The same thing can happen with data that is not random: we make more of some correlations than is actually rational, based on a subset of the data.

To prevent this from happening, it helps to do things like start out with an actual hypothesis, use legit statistical tests and other methods (think: Bayesian), and avoiding p-hacking, a way to make the data lean a certain way while still passing all the statistical tests.